| dc.creator | Vernikos I., Mathe E., Papadakis A., Spyrou E., Mylonas P. | en |
| dc.date.accessioned | 2023-01-31T10:32:20Z | |
| dc.date.available | 2023-01-31T10:32:20Z | |
| dc.date.issued | 2019 | |
| dc.identifier | 10.1145/3316782.3322740 | |
| dc.identifier.isbn | 9781450362320 | |
| dc.identifier.uri | http://hdl.handle.net/11615/80591 | |
| dc.description.abstract | In this paper we present preliminary results of an approach for understanding human actions, based on a novel 2D image representation for 3D skeletal data. More specifically, motion information for human skeletal joints is transformed to a pseudo-colored image. A Convolutional Neural Network is then used for classification. Our approach is evaluated for actions that may be used in an ambient assisted living scenario. © 2019 Association for Computing Machinery. | en |
| dc.language.iso | en | en |
| dc.source | ACM International Conference Proceeding Series | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069191168&doi=10.1145%2f3316782.3322740&partnerID=40&md5=1b7a4df1f83823b565eee446e16b1b24 | |
| dc.subject | Convolution | en |
| dc.subject | Knowledge representation | en |
| dc.subject | Action recognition | en |
| dc.subject | Ambient assisted living | en |
| dc.subject | Colored images | en |
| dc.subject | Human actions | en |
| dc.subject | Human activity recognition | en |
| dc.subject | Image representations | en |
| dc.subject | Motion information | en |
| dc.subject | Skeletal joints | en |
| dc.subject | Convolutional neural networks | en |
| dc.subject | Association for Computing Machinery | en |
| dc.title | An image representation of skeletal data for action recognition using convolutional neural networks | en |
| dc.type | conferenceItem | en |
